The analysis and management of risk as it relates to intellectual property is hampered by a paucity of sophisticated analytical tools. In the analysis of large portfolios of patents, practitioners often find great difficulty in reordering and filtering the portfolio so that the most relevant patents are brought to prominence, while the visibility of less relevant patents is diminished. One reason for the lack of sophisticated tools has been the industry's reliance on purely objective algorithms for the constitution of analytical tools. For example, Boolean searches test for the presence or absence of a set of words. Semantic searches test for a statistical distribution of words. Searches based on patent classification test for matching nomenclature. A more sophisticated approach would take in to account that by the time a practitioner conducts his or her analysis, a portfolio of patents has already been imbued with information resulting from a number of analytical decisions already made. This latent intelligence is encoded in the patent's classification, litigation history, ownership, and other events as will be described in the specification below.
For example, (1) a patent examiner has classified the subject matter of the patent using the hierarchical and information-laden International Patent Classification system (IPC). (2) Assignees of similar patents have decided to (or decided not to) pursue litigation based on the perceived value of subject matter. (3) Inventors have made a decision to patent within a particular subject area. (4) Inventors have referenced patents in other classifications within their applications. (5) Similarly, patent examiners have made decisions to cite patents within other classifications. (6) Purchasers of patents or portfolios have placed a dollar-value on patents of a particular subject matter. (7) Assignees of patents have made decisions to pay maintenance fees on patents within various classifications, some classifications perhaps more frequently than others.
In each of the above examples and in relation to other events described below, a knowledgeable individual has assessed not only the patent in question, but the subject matter to which the patent belongs. An improved set of analytical tools would make use of the latent intelligence created by these decisions. One reason for the lack of such analytical tools is that the art has, up to this point, lacked a technique for relating these decisions to one another and to the underlying subject matter. This is true despite the fact that several hierarchical classification systems have been developed for the patent system with the expressed purpose of relating specific documents to an underlying subject matter.
The present invention seeks to remedy these shortcomings by providing a method to utilize the structure of a hierarchical classification system in conjunction with the recorded and quantifiable decisions of previous individuals involved with the collective body of patents to improve the efficacy of analysis of a patent or portfolio of patents.
Hierarchical Classification System
The need for a tree-like, hierarchical taxonomical structure arises from the need to relate document of a particular subject matter to similar document and to other media within that subject matter. The tree structure is advantageous because it provides the classifier with a structured approach to the difficult task of classifying documents. Such a structure stretches the classifying decision out over several smaller, and hopefully easier, classification decisions. As such, the structure of the hierarchical classification system must be determined prior to any classification. Thus, if used properly the hierarchical classification system already conveys a tremendous amount of latent intelligence to the process of analyzing patents.
A tree-like hierarchical classification system defines a set of relationships between nodes of the tree. A node is a point of data within the structure. Each node represents a distinct and unique category. A tree structure is organized such that each node has a single “parent” node and zero or more “child” nodes. A parent node contains, or is a superclass of a child node. “Sibling” nodes have the same parent node. An “ancestor” is any node connected to a lower-level node. The topmost node is often referred to as the tree “root” and has no parent node. “Leaf” nodes are the bottom-most nodes and have no child nodes. Trees are hierarchical structures and may be considered in terms of “levels” of the tree wherein the root node forms the highest level, the children of the root form the next level, and so on.
A hierarchical classification system defines a decision tree for the classifier wherein the classifier, at each node in the decision, assigns to the subject matter one of a limited number of categories corresponding to each of the child nodes of the node. The next classifying decision is based on the child nodes of the selected node, if any exist. Early in the decision process (at the top nodes of the tree), the categories describe broad subject matter. At each subsequent level, the available categories become narrower in scope and further refine the classification of the ancestor nodes. The classification is complete when the classifier has reached a predetermined degree of specificity—usually known by the number of levels through which the decision process has traversed. In this manner, a hierarchical classification system will divide subject matter in to distinct groups in a stepwise fashion.
A hierarchical classification system is particularly useful in the analysis of patents because, in addition to providing a convenient means of classifying patentable material in to distinct groups, the taxonomic structure encapsulates information about the relationships between patent classes. For instance, patents in two different classifications which share an ancestor only one level above are more alike than those whose first common ancestor is closer to the root of the tree. This is intuitively similar to the commonplace understanding of the similarity between patentable subjects. For example, an invention claiming a method of polymerizing organic molecules has greater similarity to an invention claiming a method of inorganic synthesis than it does to an invention claiming a method of manufacturing an engine block. This idea of similarity, based on a classification's position within the tree structure, is a greatly underused advantage of a hierarchical classification system.
Thus, such classification systems which encapsulate the collective, thoughtful and intelligent input of skilled persons, capture and transmit a tremendous quantity of information about patents within its structure alone. In particular, they embody decisions made by informed examiners with expertise in the hierarchical classifying system to assign a patent to a particular classification. The present invention seeks to make maximal use of the information in that decision, transmitted by the assignment of a patent to a patent class, to quickly rank and qualify a patent during analysis. One hierarchical classification system, the International Patent Classification (IPC) is very useful in this endeavor. While, slightly more complex than the ideal tree structure described above, the IPC is a convenient and widely used hierarchical classification system for patents and will be used in the forgoing discussion of the present invention so to provide a concrete example of how the present invention could be implemented. Of course, the IPC is not necessary for this invention. Any hierarchical classifying system may be used. The IPC, however, is convenient in that it is widely employed and supported internationally and is under active development.
The latest intelligence of the IPC and other like complicated systems or collections of decisions can be mined to create a heuristic rule system which enables the user, using a computer, to determine the relationships between the levels of the taxonomy which are the collective, latent intelligence of hundreds of not thousands of individuals.
International Patent Classification (IPC)
In the IPC, high-level nodes represent broad categorizations of patentable subject matter. Child nodes always represent categorizations which are narrower in scope than categorization of their parent node. By doing so, an examiner may classify the subject matter of a document in a stepwise fashion, assigning a broad category to the subject matter, followed by a narrower child classification, and so on until a complete class symbol has been constructed.
In the IPC, the layers are given the names: Section, Class, Subclass, Group, and Main/Sub group. At each level of classification, the examiner adds the symbol of the node to the burgeoning class symbol. The section symbol is a letter from A (“Human Necessities”) to H (“Electricity”). The Class symbol is a two-digit number. The subclass is a letter. Groups are given a 1-3 digit number while the main/subgroup is assigned a number of at least two digits. If this final symbol is ‘00’ then the group is considered a main group. With any other number, it is a subgroup.
The combination of all these symbols represents a complete classification. For example, in the classification A61B 18/00, ‘A’ represents the ‘Human Necessities’ section. ‘A61’ represents the “Medical or Veterinary Science; Hygiene” class. ‘A61B’ refers to the “Diagnosis; Surgery; Identification” subclass. And the entire symbol represents the classification “Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body.” The ‘00’ means this is a main group.
At first glance, it appears that there are only five layers in this tree structure. The IPC, however, is a complicated system and the logical relationship between main groups and subgroups does not necessarily match what is textually suggested by the complete classification symbol. Unlike Section, Classes, and Subclasses whose symbols do not represent complete classification symbols, main and subgroups do represent complete symbols AND can be parents and/or ancestors of a plurality of subgroups. This relationship is not reflected in the complete classification symbol, but can be deciphered from the number of stars preceding the title text of the subgroup. For example, a subclass with three stars before its title text is a child of the closest two-star subclass with a lesser subgroup number.
For a more complete description of the IPC, please see the IPC documentation at http://www.wipo.int/classifications/en/.